How AI Is Changing Animation Jobs, Workflows, and Creative Control

Artificial intelligence (AI) art tools are flooding the market with promises to revolutionize creative workflows, but many animators report feeling like these tools don't actually fit how they work. As the entertainment industry grapples with how to integrate AI into production pipelines, questions about control, craft, and quality have become urgent.

Moshe (Mo) Mahler, assistant teaching professor at Carnegie Mellon University's Entertainment Technology Center, teaches animation, storytelling, and interactive media. He draws on his experience as an award-winning innovator and storyteller whose work has been featured in Disney Parks and Resorts attractions and presented worldwide at venues including UIST, Comic Con, and Ars Electronica. Mahler's animated short film, “The Art of Weightlessness,” won Best in Show at SIGGRAPH 2024 and qualified for an Academy Award.

His recent paper, “The Evolution of Artists' Toolsets: A Call for Artist-Driven Design,” examines why current AI art tools often miss the mark with professional animators and proposes principles for building tools that actually support artistic practice.

Why do many AI animation tools struggle to fit into professional animation workflows?

Many AI animation tools struggle to fit professional workflows because in the animation industry, we typically focus on two things when improving our toolsets: quality and efficiency. AI tools offer an exciting opportunity to improve both, allowing animators to work faster while producing high-quality outputs. But Generative AI, as it stands today, ignores another key principle of artist-driven design: control.

Animation is fundamentally a medium of control. Everything the audience sees is carefully planned and executed by the animator to maximize the animation's performance and tell the story as appealingly as possible. When you remove that control, you're inherently left with a lower-quality experience.

How did the shift from 2D to 3D animation force artists to adapt to new creative tools?

The shift from 2D to 3D animation in the late 1990s and early 2000s is a perfect example of how new creative tools forced artists to adapt. The animation industry experienced a major technological disruption as 3D animation production overtook traditional hand-drawn workflows. When studios like Disney Animation shifted from hand-drawn to computer-based 3D workflows, many animators either failed to adapt or didn't want to. This disruption was partly due to the introduction of complex user interfaces and the transfer of known artistic practices to unfamiliar technical solutions.

For example, a 2D animator might have mastered the principle of "timing and spacing"— dictating how fast an object moves through space. In 3D animation, movement is controlled through graphs instead of drawings. So even though the concept is the same, the tool feels completely different.

When I was a kid, I would make little flip books of animated drawings on Post-it note pads. No one taught me to do this, but figuring out how to make an animation this way was simple enough. Now, there's a significant barrier to entry to modern 3D animation workflows. It takes several specialized job roles, some of which are very technical, just to bring a character performance to life.

How is AI being used in the animation industry today, including outsourcing, labor, and production pipelines?

To understand how AI is affecting animation jobs, outsourcing, and production pipelines in the global animation industry, you have to start with the economics of animation. Animation sets itself apart from other art forms because it's comparatively very slow and time-consuming. It takes animators years of experience to create professional-quality work. So the traditional model for creating an animated film is to hire a large team of experienced animators over several years to produce a 90-minute film, which typically costs $150 million or more.

This high cost creates different paradigms for animation production worldwide. Television animation, for example, has long rethought this model to create lower-quality animation much more quickly, making weekly content possible. Modern TV animation is typically outsourced overseas to create content faster and cheaper.

This creates an opening for AI to impact these different animation paradigms. It's much more likely that studios will relinquish control over visual storytelling to achieve faster gains in production for a children's animated television show than for a feature film. But even feature film studios are constantly evolving their workflows to integrate new technologies.

Currently, AI is well-suited to support visual development, concept work, and preproduction, but we still lack adequate tooling to integrate it into animation production in a meaningful way. It's much more likely to create animation opportunities for non-animators, such as TikTok or YouTube content creators, for example. Impact on studio production may come sooner if AI can integrate itself into proper workflows. Imagine if a director could draw corrections right on top of an animated scene, and the software would automatically update the character’s movement for the animator to refine. I often tell our students that "full automation is not the goal, because semi-automation is often much more powerful."

What principles should guide the design of AI tools for animators?

When designing AI tools for animators, we still don’t fully know where AI stands as an effective artistic tool. But I'm hopeful that we'll see a redesign of modern workflows from the ground up, because AI has tremendous potential to aid the craft of animation. Think about paint as an interface. A child can sit in front of a canvas and begin to work, yet it takes a lifetime to master painting. This is the core idea of artist-centered design: technology shouldn't be at the forefront of the creation process. Instead, technology should blend into the background to support the artist's intent and craftsmanship.

We believe the following principles form the foundation of artist-centered design: quality, efficiency, control, enjoyment, the potential for mastery, and the ability to meet artists in their natural workflows. If AI can integrate these principles equally, it should have a lasting impact on most art forms and change how we tell stories for years to come.